Task Motivation and Engagement in Second Language Acquisition: A Structural Equation Modelling Analysis

ABSTRACT The last two decades have witnessed a growing interest among scholars in exploring the conceptualization, operationalization, and measurement of second language (L2) task engagement in diverse educational settings. However, the concept is still not clearly defined and remains complex. Clarifying this complexity is crucial for developing a valid theory of task engagement in second language acquisition (SLA). One prominent issue in capturing the complexity of L2 task engagement is its intricate relationship with task motivation. To address this issue, a structural equation modelling (SEM) analysis was conducted to investigate whether and to what extent task motivation, characterised by intrinsic motivation, identified regulation, external regulation, and amotivation, correlates with task engagement—behavioural, cognitive, emotional, social, and agentic—in Iran, where English is considered a foreign language (EFL). The findings suggested that intrinsic motivation and identified regulation were strongly linked to learner engagement in L2 tasks. In contrast, external regulation had weaker correlations, indicating that intrinsic factors were more important than extrinsic pressures and rewards in predicting task engagement in L2 learning. Overall, the findings suggested that L2 learners' intrinsic motivation and their perception of the importance and value of the task determined the extent and quality of their task engagement.

Authors

Institutions

Publication Details

Journal
European Journal of Education
Published
2025-11-14
DOI
https://doi.org/10.1111/ejed.70353
Citations
1
Primary Topic
EFL/ESL Teaching and Learning
Type
article
Field-Weighted Citation Impact
10.42
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Task Motivation and Engagement in Second Language Acquisition: A Structural Equation Modelling Analysis

Javad Zare, Ali Derakhshan, Fatemeh Ranjbaran
1 citations
European Journal of Education
EFL/ESL Teaching and Learning
10.42
article

Task Motivation and Engagement in Second Language Acquisition: A Structural Equation Modelling Analysis

Javad Zare, Ali Derakhshan, Fatemeh Ranjbaran
article en
1 citations

Abstract

ABSTRACT The last two decades have witnessed a growing interest among scholars in exploring the conceptualization, operationalization, and measurement of second language (L2) task engagement in diverse educational settings. However, the concept is still not clearly defined and remains complex. Clarifying this complexity is crucial for developing a valid theory of task engagement in second language acquisition (SLA). One prominent issue in capturing the complexity of L2 task engagement is its intricate relationship with task motivation. To address this issue, a structural equation modelling (SEM) analysis was conducted to investigate whether and to what extent task motivation, characterised by intrinsic motivation, identified regulation, external regulation, and amotivation, correlates with task engagement—behavioural, cognitive, emotional, social, and agentic—in Iran, where English is considered a foreign language (EFL). The findings suggested that intrinsic motivation and identified regulation were strongly linked to learner engagement in L2 tasks. In contrast, external regulation had weaker correlations, indicating that intrinsic factors were more important than extrinsic pressures and rewards in predicting task engagement in L2 learning. Overall, the findings suggested that L2 learners' intrinsic motivation and their perception of the importance and value of the task determined the extent and quality of their task engagement.

European Journal of EducationVol. 60(4)
Golestan University (IR), Kosar University of Bojnord (IR), Sultan Qaboos University (OM)
Openalex Percentile: Top 2%
EFL/ESL Teaching and Learning
10.42
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.